Genetic algorithm (GA) is a search-based optimization technique whose fundamentals come from the theory of genetics and natural selection. It is used to solve optimization problems in research and machine learning areas which are very difficult and time-consuming solutions by alternative methods.
Optimization is the process of finding a solution which is better when compared to all other alternative solutions. It takes the space of all the possible solutions as search space, and then finds a solution which is most suited to the problem.
In GA, possible candidate solutions constitute the population and they recombine and mutate to produce new children, and this process is repeated over various generations. Each possible candidate solution is given a fitness value based upon the objective function. The fitter probable candidates are given preference for recombination and mutation to yield fitter candidate solutions.
Some of the most important terminology associated with GA...
